## Python机器学习课程（代码与教程）

5 月 13 日 专知

github:

https://github.com/machinelearningmindset/machine-learning-course

• 简介

• 目的

• 机器学习

• 机器学习基础

• 监督学习

• 非监督学习

• 深度学习

• 机器学习的定义

• 开始和发展趋势

• 机器学习的分类和子类

• 机器学习中最常用的算法，以及如何实现这些算法

01

1. 线性回归

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/overview/linear_regression

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/overview/linear-regression.rst

2. 过拟合/欠拟合

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/overview/overfitting

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/overview/overfitting.rst

3. 正则化

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/overview/regularization

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/overview/regularization.rst

4. 交叉验证

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/overview/cross-validation

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/overview/crossvalidation.rst

02

1. 决策树

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/supervised/DecisionTree/decisiontrees.py

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/supervised/decisiontrees.rst

2. K近邻

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/supervised/KNN/knn.py

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/supervised/knn.rst

3. 朴素贝叶斯

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/supervised/Naive_Bayes

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/supervised/bayes.rst

4. 逻辑回归

https://github.com/machinelearningmindset/machine-learning-course/blob/master/supervised/Logistic_Regression/logistic_ex1.py

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/supervised/logistic_regression.rst

5. 支持向量机

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/supervised/Linear_SVM/linear_svm.py

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/supervised/linear_SVM.rst

03

1. 聚类

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/unsupervised/Clustering

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/unsupervised/clustering.rst

2. 主成分分析

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/unsupervised/PCA

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/unsupervised/pca.rst

04

1. 神经网络概览

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/deep_learning/mlp

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/deep_learning/mlp.rst

2. 卷积神经网络

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/deep_learning/cnn

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/deep_learning/cnn.rst

3. 自编码器

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/deep_learning/autoencoder

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/deep_learning/autoencoder.rst

4. 循环神经网络

https://github.com/machinelearningmindset/machine-learning-course/blob/master/docs/source/content/deep_learning/autoencoder.rst

https://github.com/machinelearningmindset/machine-learning-course/blob/master/code/deep_learning/rnn/rnn.ipynb

Creator: Machine Learning Mindset

Supervisor: Amirsina Torfi

Developers: Brendan Sherman*, James E Hopkins* , Zac Smith

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